Numerical Tools for analyzing cell signalling circuits in normal and tumor cells

用于分析正常细胞和肿瘤细胞中细胞信号传导回路的数值工具

• 批准号: 7670716
• 负责人: PAUL J. JASPER
• 金额: $ 15万
• 依托单位: NUMERICA TECHNOLOGY, INC.
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7670716
• 关键词: Address; Algorithms; Area; Attention; Award; Biological; Biological Models; Biological Process; Biology; Breast Cancer Cell; Calibration; Case Study; Cellular biology; Chemical Models; Classification; Clinical Trials Design; Collaborations; Complex; Computer software; Data; Decision Making; Development; Discipline; Drug Delivery Systems; Engineering; Environment; Equation; Goals; Hand; Inhibitory Concentration 50; Intuition; Kinetics; Language; Link; Lung; Malignant Neoplasms; Mathematics; Methodology; Methods; Modeling; Output; Pathway interactions; Pharmaceutical Preparations; Pharmacology; Phase; Principal Investigator; Process; Property; Reaction; Sampling; Science; Scientist; Signal Pathway; Signal Transduction; Signal Transduction Pathway; Simulate; Small Business Technology Transfer Research; Software Tools; Structure; System; Systems Biology; Testing; Therapeutic; Therapeutic Index; Time; Validation; Work; Writing; base; biochemical model; cancer cell; computer science; computerized data processing; drug discovery; flexibility; follow-up; innovation; medical schools; member; model development; neoplastic cell; programs; protein complex; research and development; simulation; small molecule; software development; theories; tool

DESCRIPTION (provided by applicant): Numerical Tools for analyzing cell signaling circuits in normal and tumor cells The proposal, part I of a phased STTR award, describes the development of software tools, workflow and proof-of-principle case studies for detailed kinetic modeling of cell signaling pathways (and similarly complex biological processes). The most critical step in building kinetic models of real biological processes is optimizing the match between model prediction and experimental data. Achieving this optimization requires efficient means to explore alternative pathway topologies (which give rise to the structure of the model) and to "calibrate" models to data (which constrains model parameters). We address both of these problems with particular emphasis on the algorithms and software needed to perform calibration of highly parametric models based on deterministic ordinary differential equations. The size of these models, the incompleteness of experimental data, and the wide range of time scales makes effective extremely calibration challenging both in theory and in practice, making the proposal innovative and significant with respect to both its biology and its applied mathematics The project is a close collaboration between a software company (Numerical) with deep expertise in chemical modeling, combustion engineering and numerical simulation and two systems biology groups (Sorger and Gunawardena) with expertise in experimental biology and computer science respectively. Three phase I specific aims include (1) Development of the Lisp-based little b programming environment as a means to represents biological pathways and multi-component protein complexes in a rapidly- revised, reusable form suitable (2) Optimizing numerical analysis tools for calibration of biological models with a sophisticated workflow and new algorithms for adjoint-based sensitivity analysis and global parameter estimation (3) Methods for validating models and applying key findings to significant problems in systems pharmacology and drug discovery.

描述(由申请人提供)：用于分析正常细胞和肿瘤细胞中细胞信号通路的数值工具该提案是一项阶段性STTR奖的第一部分，描述了用于对细胞信号通路(以及类似的复杂生物过程)进行详细的动力学建模的软件工具、工作流程和原则证明案例研究的开发。建立真实生物过程动力学模型最关键的一步是优化模型预测与实验数据之间的匹配。实现这一优化需要有效的手段来探索替代的路径拓扑(这导致了模型的结构)，并将模型“校准”到数据(这约束了模型参数)。我们解决了这两个问题，特别强调了执行基于确定性常微分方程式的高参数模型校准所需的算法和软件。这些模型的规模、实验数据的不完全性和广泛的时间范围使得有效的校准在理论和实践中都具有极大的挑战性，这使得该建议在其生物学和应用数学方面具有创新性和重要意义。该项目是一个在化学建模、燃烧工程和数值模拟方面拥有深厚专业知识的软件公司(Numerical)与分别在实验生物学和计算机科学方面拥有专业知识的两个系统生物学小组(Sorger和Gunawdena)之间的密切合作。第一阶段的三个具体目标包括(1)开发基于LISP的小B编程环境，作为以一种快速修订的、可重复使用的形式表示生物通路和多组分蛋白质复合体的手段；(2)利用复杂的工作流程以及用于基于伴随的敏感性分析和全局参数估计的新算法来优化用于校准生物模型的数值分析工具；(3)用于验证模型并将关键发现应用于系统药理学和药物发现中的重大问题的方法。